Home > Archive > 2020 > Volume 10 Number 3 (May 2020) >
IJMLC 2020 Vol.10(3): 477-481 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2020.10.3.960

A Standardized Bare Bones Particle Swarm Optimization Algorithm for Traveling Salesman Problem

Jia Guo and Yuji Sato

Abstract—The traveling salesman problem (TSP) plays an important role in theoretical computer science. It can be used to solve different route planning problems in the real world and has been proved to be NP-hard. Plenty of researchers tried to solve the TSP by the population-based algorithms. However, as a real-world problem, the TSP has two major differences with the benchmark functions. One is the visiting order of the TSP is a combination of integers and the other one is each city in the problem has to be exactly visited once. To cross the two problems, the standardized bare bones particle swarm optimization (SBBPSO) algorithm is proposed in this work. The Gaussian distribution is used to select the positions of particles in the next generation. A standardized converter is used to ensure the dimensions of each particle are integers and each city has been visited exactly once. To test the performance of the SBBPSO, several famous instances are used in the experiments. Also, the standard bare bones particle swarm optimizations algorithm is used as the control group. The experimental results confirm that the SBBPSO is able to solve the TSP.

Index Terms—Bare bones, particle swarm optimization, standardized, traveling salesman problem.

Jia Guo is with the Graduate School of Computer and Information Sciences, Hosei University, Tokyo, Japan (e-mail: guojia314@gmail.com).
Yuji Sato is with the Faculty of Computer and Information Sciences, Hosei University, Tokyo, Japan (e-mail: yuji@hosei.ac.jp).

[PDF]

Cite: Jia Guo and Yuji Sato, "A Standardized Bare Bones Particle Swarm Optimization Algorithm for Traveling Salesman Problem," International Journal of Machine Learning and Computing vol. 10, no. 3, pp. 477-481, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net


Article Metrics